Method, apparatus, and system with resist image estimation

Abstract

A method and apparatus for estimating a resist image (RI) are disclosed. The method includes obtaining an aerial image (AI) and a first RI from a mask image (MI), obtaining a second RI from the AI, and obtaining a third RI based on the first RI and the second RI.

What is claimed is: 
     
         1 . A method of estimating a resist image (RI), the method comprising:
 obtaining an aerial image (AI) and a first RI from a mask image (MI);   obtaining a second RI by inputting the AI to an additional kernel model; and   obtaining a third RI based on the first RI and the second RI,   wherein the third RI comprises shape information of a pattern formed on a wafer that is generated by the MI.   
     
     
         2 . The method of  claim 1 , wherein the obtaining of the AI and the first RI comprises obtaining the AI and the first RI by inputting the MI to a compact model. 
     
     
         3 . The method of  claim 1 , wherein the obtaining of the third RI comprises obtaining the third RI by combining the first RI with the second RI. 
     
     
         4 . The method of  claim 1 , wherein the additional kernel model is trained based on a difference between a resist contour image (RCI) generated based on the third RI and a measurement contour image generated through measurement. 
     
     
         5 . The method of  claim 4 , wherein the additional kernel model is trained so that the difference is minimized through backpropagation. 
     
     
         6 . The method of  claim 1 , further comprising:
 obtaining a predicted mask layout based on the third RI; and   correcting a mask layout based on a difference between the predicted mask layout and a target mask layout.   
     
     
         7 . The method of  claim 6 , wherein the obtaining of the predicted mask layout further comprises:
 generating an RCI from the third RI; and   obtaining the predicted mask layout based on the RCI.   
     
     
         8 . The method of  claim 6 , wherein the correcting of the mask layout further comprises:
 correcting the mask layout based on the difference between the predicted mask layout and the target mask layout; and   obtaining a mask layout image that is rasterized from the corrected mask layout.   
     
     
         9 . The method of  claim 8 , further comprising:
 generating an MI in which a three-dimensional (3D) element is reflected by inputting the mask layout image to a mask model.   
     
     
         10 . A method of manufacturing a mask, the method comprising:
 obtaining a resist image (RI) by inputting a mask image (MI) to an RI estimation model;   obtaining a predicted mask layout based on the RI; and   correcting a mask layout based on a difference between the predicted mask layout and a target mask layout,   wherein the RI comprises shape information of a pattern formed on a wafer that is generated by the MI.   
     
     
         11 . A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the method of  claim 1 . 
     
     
         12 . An electronic device comprising:
 a memory storing at least one instruction; and   a processor configured to, by executing the at least one instruction stored in the memory:
 obtain an aerial image (AI) and a first resist image (RI) from a mask image (MI); 
 obtain a second RI by inputting the AI to an additional kernel model; and 
 obtain a third RI based on the first RI and the second RI, 
   wherein the third RI comprises shape information of a pattern formed on a wafer that is generated by the MI.   
     
     
         13 . The electronic device of  claim 12 , wherein the processor is configured to obtain the AI and the first RI by inputting the MI to a compact model. 
     
     
         14 . The electronic device of  claim 12 , wherein the processor is configured to obtain the third RI by combining the first RI with the second RI. 
     
     
         15 . The electronic device of  claim 12 , wherein the additional kernel model is trained based on a difference between a resist contour image (RCI) generated based on the third RI and a measurement contour image generated through measurement. 
     
     
         16 . The electronic device of  claim 15 , wherein the additional kernel model is trained so that the difference is minimized through backpropagation. 
     
     
         17 . The electronic device of  claim 15 , wherein the processor is configured to:
 obtain a predicted mask layout based on the third RI; and   correct a mask layout based on a difference between the predicted mask layout and a target mask layout.   
     
     
         18 . The electronic device of  claim 17 , wherein the processor is configured to:
 generate the RCI from the third RI; and   obtain the predicted mask layout based on the RCI.   
     
     
         19 . The electronic device of  claim 17 , wherein the processor is configured to:
 correct the mask layout based on the difference between the predicted mask layout and the target mask layout; and   obtain a mask layout image that is rasterized from the corrected mask layout.   
     
     
         20 . The electronic device of  claim 19 , wherein the processor is configured to generate an MI in which a three-dimensional (3D) element is reflected by inputting the mask layout image to a mask model.